Suchergebnisse - "generalized expectation maximization algorithm"

Neutron source reconstruction using a generalized expectation-maximization algorithm on one-dimensional neutron images from the Z facility von Ricketts, S A, Mangan, M A, Volegov, P, Fittinghoff, D N, Lewis, W E, Mannion, O M, Morel, J E, Adams, M L, Ampleford, D J

“… Here, we present a modified generalized expectation-maximization algorithm to reconstruct an axial neutron emission profile of the stagnated fusion plasma …”
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sMLACF: a generalized expectation-maximization algorithm for TOF-PET to reconstruct the activity and attenuation simultaneously von Salvo, Koen, Defrise, Michel

“… The 'simultaneous maximum-likelihood attenuation correction factors' (sMLACF) algorithm presented here, is an iterative algorithm to calculate the …”
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Space-alternating generalized expectation-maximization algorithm von Fessler, J.A., Hero, A.O.

“… The expectation-maximization (EM) method can facilitate maximizing likelihood functions that arise in statistical estimation problems. In the classical EM …”
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In vitro estimation of fast and slow wave parameters of thin trabecular bone using space-alternating generalized expectation–maximization algorithm von Grimes, Morad, Bouhadjera, Abdelmalek, Haddad, Sofiane, Benkedidah, Toufik

“… ► The wave propagation in thin trabecular bone is performed using Biot’s FDTD method. ► The Biot’s fast and slow waves are superimposed. ► The SAGE algorithm …”
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Multiple testing for neuroimaging via hidden Markov random field von Shu, Hai, Nan, Bin, Koeppe, Robert

“… A generalized expectation–maximization algorithm for maximizing the penalized likelihood is proposed for estimating the model parameters …”
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Research on Multi-Parameter Optimization of Indoor WiFi Positioning Technology von WANG Yingying, CHANG Jun, WU Hao

“… On this basis, the Space Alternating Generalized Expectation Maximization algorithm(SAGE) is used to refine the wrong original parameters to a narrow …”
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Generalized expectation–maximization approach to LPV process identification with randomly missing output data von Yang, Xianqiang, Huang, Biao, Zhao, Yujia, Lu, Yaojie, Xiong, Weili, Gao, Huijun

“… This paper considers parameter estimation for linear parameter varying (LPV) systems with randomly missing output data. The multi-model LPV model is adopted …”
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Asynchronous Linear Modulation Classification With Multiple Sensors via Generalized EM Algorithm von Ozdemir, Onur, Wimalajeewa, Thakshila, Dulek, Berkan, Varshney, Pramod K., Wei Su

“… In this paper, we consider the problem of automatic modulation classification with multiple sensors in the presence of unknown time offset, phase offset and …”
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Maximum weighted likelihood estimator for robust heavy-tail modelling of finite mixture models von Fung, Tsz Chai

“… Insurance claim severity data are characterized by complex distributional phenomenons, where flexible density estimation tools such as the finite mixture …”
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Model-Based Clustering and Classification Using Mixtures of Multivariate Skewed Power Exponential Distributions von Dang, Utkarsh J., Gallaugher, Michael P.B., Browne, Ryan P., McNicholas, Paul D.

“… Families of mixtures of multivariate power exponential (MPE) distributions have already been introduced and shown to be competitive for cluster analysis in …”
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Self-tuning robust adjustment within multivariate regression time series models with vector-autoregressive random errors von Kargoll, Boris, Kermarrec, Gaël, Korte, Johannes, Alkhatib, Hamza

“… The iteratively reweighted least-squares approach to self-tuning robust adjustment of parameters in linear regression models with autoregressive (AR) and …”
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Deep GEM-Based Network for Weakly Supervised UWB Ranging Error Mitigation von Li, Yuxiao, Mazuelas, Santiago, Shen, Yuan

“… Ultra-wideband (UWB)-based techniques, while becoming mainstream approaches for high-accurate positioning, tend to be challenged by ranging bias in harsh …”
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Underdetermined Convolutive Source Separation Using GEM-MU With Variational Approximated Optimum Model Order NMF2D von Al-Tmeme, Ahmed, Woo, Wai Lok, Dlay, Satnam Singh, Gao, Bin

“… An unsupervised machine learning algorithm based on nonnegative matrix factor Two-dimensional deconvolution (NMF2D) with approximated optimum model order is …”
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Analysis of a Generalized Expectation-Maximization Algorithm for Gaussian Mixture Models: A Control Systems Perspective von Chatterjee, Sarthak, Romero, Orlando, Pequito, Sérgio

“… The Expectation-Maximization (EM) algorithm is one of the most popular methods used to solve the problem of parametric distribution-based clustering in …”
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Distributed asynchronous modulation classification based on hybrid maximum likelihood approach von Wimalajeewa, Thakshila, Jagannath, Jithin, Varshney, Pramod K., Drozd, Andrew, Wei Su

“… In this paper, we consider the problem of automatic modulation classification (AMC) with multiple sensors. A distributed hybrid maximum likelihood (HML) based …”
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Hammerstein System Identification with Skewed and Asymmetric Noise von Wang, Chen, Liu, Xin

“… To eliminate the negative effect brought by the skewed and asymmetric measurement noise, this paper proposes a robust identification algorithm for the …”
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Channel Parameter Extraction Based on BP-Neural Network in NLOS Environment von Hu, Zhexin, Bu, Fanliang, Ding, Dandan

“… expectation-maximization algorithm. The results show that the back-propagation neural network model algorithm works well and can be used for channel parameter extraction …”
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Joint Channel Estimation, Interference Cancellation, and Data Detection for Ambient Backscatter Communications von Darsena, Donatella, Gelli, Giacinto, Verde, Francesco

“… The proposed technique, which relies on the space alternating generalized expectation maximization algorithm, detects the backscatter symbols iteratively, while the channel parameters are updated …”
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Synergetically generalized expectation maximization algorithm for ECT von Peter, J., Smith, M.F., Scarfone, C., Jaszczak, R.J., Coleman, R.E.

“… A synergetically generalized expectation maximization (SGEM) reconstruction algorithm is proposed, which builds on the expectation maximization approach to …”
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A row-action alterative to the space-alternating generalized expectation-maximization algorithm for image reconstruction in positron emission tomography von Zhu Hongqing, Shu Huazhong, Luo Limin, Zhou Jian

“… The space-alternating generalized expectation (SAGE) maximization algorithm has been successfully used in image reconstruction due to its rapid convergence. In …”
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